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arXiv 1104.2132math.COcs.DM
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关于随机图的树深

On the tree-depth of Random Graphs

Guillem Perarnau, Oriol Serra

摘要:

树深度是一个参数,它有几个名字,用来度量图的稀疏性。我们计算了随机图的树深度的渐近值。对于稠密图,p>> 1/n,随机图G的树深是a.a.s. td(G)=n-O(sqrt(n/p)). p=c/n的随机图有a.a.s.当c&gt;1时,树的深度是线性的,当c=1时,树的深度是Theta(logn),而对于c 1的Theta(loglogn)<1. The result for c>是由树的宽度计算得来的,这为Lee,Lee和Oum最近证明的Gao关于树的宽度的线性性的猜想提供了一个更直接的证明.我们还证明,对于c=1,每个宽度参数都是a.a.s.。常数,随机正则图具有线性树深。

英文摘要:

The tree-depth is a parameter introduced under several names as a measure of sparsity of a graph. We compute asymptotic values of the tree-depth of random graphs. For dense graphs, p>> 1/n, the tree-depth of a random graph G is a.a.s. td(G)=n-O(sqrt(n/p)). Random graphs with p=c/n, have a.a.s. linear tree-depth when c>1, the tree-depth is Theta (log n) when c=1 and Theta (loglog n) for c<1. The result for c>1 is derived from the computation of tree-width and provides a more direct proof of a conjecture by Gao on the linearity of tree-width recently proved by Lee, Lee and Oum. We also show that, for c=1, every width parameter is a.a.s. constant, and that random regular graphs have linear tree-depth.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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